Genetically-predicted prefrontal DRD4 gene expression modulates differentiated brain responses to food cues in adolescent girls and boys
Bibliographic record
Abstract
The dopamine receptor 4 (DRD4) in the prefrontal cortex (PFC) acts to modulate behaviours including cognitive control and motivation, and has been implicated in behavioral inhibition and responsivity to food cues. Adolescence is a sensitive period for the development of habitual eating behaviors and obesity risk, with potential mediation by development of the PFC. We previously found that genetic variations influencing DRD4 function or expression were associated with measures of laboratory and real-world eating behavior in girls and boys. Here we investigated brain responses to high energy-density (ED) and low-ED food cues using an fMRI task conducted in the satiated state. We used the gene-based association method PrediXcan to estimate tissue-specific DRD4 gene expression in prefrontal brain areas from individual genotypes. Among girls, those with lower vs. higher predicted prefrontal DRD4 expression showed lesser activation to high-ED and low-ED vs. non-food cues in a distributed network of regions implicated in attention and sensorimotor processing including middle frontal gyrus, and lesser activation to low-ED vs non-food cues in key regions implicated in valuation including orbitofrontal cortex and ventromedial PFC. In contrast, males with lower vs. higher predicted prefrontal DRD4 expression showed minimal differences in food cue response, namely relatively greater activation to high-ED and low-ED vs. non-food cues in the inferior parietal lobule. Our data suggest sex-specific effects of prefrontal DRD4 on brain food responsiveness in adolescence, with modulation of distributed regions relevant to cognitive control and motivation observable in female adolescents.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".